Struct Transformer

pub struct Transformer { /* private fields */ }

Implements a standard Transformer model.

The implementation is based on “Attention Is All You Need” https://arxiv.org/abs/1706.03762.

The Transformer model contains an encoder and a decoder. The encoder processes the input sequence and the decoder generates the output sequence. The interaction between encoder and decoder happens through the attention mechanism.

Implementations

impl Transformer

pub fn new() -> Result<Self, <<Self as Buildable>::Builder as Builder<Self>>::Error>

Creates a new instance of Transformer.

impl Transformer

pub const DEFAULT_DIMENSIONS: i32 = 512i32

Default value for dimensions

pub const DEFAULT_NUM_HEADS: i32 = 8i32

Default value for num_heads

pub const DEFAULT_ENCODER_LAYERS_COUNT: usize = 6usize

Default number of encoder layers

pub const DEFAULT_DECODER_LAYERS_COUNT: usize = 6usize

Default number of decoder layers

pub const DEFAULT_DROPOUT: f32 = 0f32

Default value for dropout

pub const DEFAULT_NORM_FIRST: bool = false

Default value for activation

Trait Implementations

impl Buildable for Transformer

type Builder = TransformerBuilder

The builder type for this buildable type

impl Builder<Transformer> for TransformerBuilder

type Error = TransformerBulidError

Error with building

fn build(self) -> Result<Transformer, Self::Error>

Build the type

impl Clone for Transformer

fn clone(&self) -> Transformer

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Transformer

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'a, Input> Module<Input> for Transformer

where Input: Into<TransformerInput<'a>>,

type Error = Exception

Error type for the module.

type Output = Array

Output type of the module.

fn forward(&mut self, input: Input) -> Result<Self::Output, Self::Error>

Forward pass of the module.

fn training_mode(&mut self, mode: bool)

Set whether the module is in training mode.

impl ModuleParameters for Transformer

fn freeze_parameters(&mut self, recursive: bool)

Freeze all parameters in the module.

fn unfreeze_parameters(&mut self, recursive: bool)

Unfreeze all parameters in the module.

fn parameters(&self) -> ModuleParamRef<'_>

Get references to the module parameters.

fn parameters_mut(&mut self) -> ModuleParamMut<'_>

Get mutable references to the module parameters.

fn trainable_parameters(&self) -> ModuleParamRef<'_>

Get references to the trainable parameters. A parameter is trainable if it is NOT frozen.

fn all_frozen(&self) -> Option<bool>

Check if all parameters in the module are frozen. Returns None if there are no parameters.

fn any_frozen(&self) -> Option<bool>

Check if any parameter in the module is frozen. Returns None if there are no parameters.

fn update(&mut self, parameters: ModuleParam)

Update the module parameters.

fn update_flattened(&mut self, flattened_parameters: FlattenedModuleParam)

Update the module parameters from a flattened representation.

impl Quantizable for Transformer

type Quantized = Transformer

The quantized type.

type QuantizationError = Exception

The error type for quantization.

fn try_into_quantized( self, group_size: i32, bits: i32, ) -> Result<Self::Quantized, Self::QuantizationError>

Quantize the module with the specified group size and number of bits.

const DEFAULT_GROUP_SIZE: i32 = 64i32

The default group size for quantization.

const DEFAULT_BITS: i32 = 4i32

The default number of bits for quantization.